Fig 1.
Diagram of the analysis workflow.
Fig 2.
Salmonella and M. tuberculosis dataset UMAP projections before batch effect correction and after batch effect correction.
On the left the cells are colored according to the dataset they are derived from; on the right the cells are colored according to cell type.
Fig 3.
Violin plot presenting the distribution of effect size ratio values for monocytes between Salmonella stimulated and control samples.
Each dot represents a gene effect size ratio value. The dots marked in red correspond to the cluster-specific genes for monocytes indicated in [28].
Table 1.
Weighted Dice-Sørensen index (DSI) values for the comparison of cluster assignments between the original identification in [30] and the clusters determined by DivIK.
Fig 4.
Correlogram showing Spearman’s correlation between pairs of main cell types based on their effect size profiles in the two studies species.
The highest positive correlation coefficient indicates pairing cell types for naked mole rat in reference to the mouse saline treated sample.
Table 2.
Data set sizes for human and bovine samples.
Fig 5.
Correlograms for effect size profile vectors between human and bovine samples.
The strongest positive correlation indicates a link between clusters and may serve as an indicator of homologous clusters in different species. (a) Control samples, (b) Stimulated samples.
Fig 6.
Mean expression values for genes chosen with a high effect size profile in monocytes for scRNA-seq and qPCR experiments.
The control samples are marked in red, the stimulated samples in green. The immune response observed in the scRNA-seq experiments is coherent with the results of qPCR analysis.